Pinned Repositories
cider
PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023
dream-ood
source code for NeurIPS'23 paper "Dream the Impossible: Outlier Imagination with Diffusion Models"
gradnorm_ood
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
knn-ood
Code for ICML 2022 paper "Out-of-distribution Detection with Deep Nearest Neighbors"
large_scale_ood
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
MCM
PyTorch implementation of MCM (Delving into out-of-distribution detection with vision-language representations), NeurIPS 2022
npos
source code for ICLR'23 paper "Non-parametric Outlier Synthesis"
react
Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"
stud
source code for CVPR'22 paper "Unknown-Aware Object Detection: Learning What You Don’t Know from Videos in the Wild"
vos
source code for ICLR'22 paper "VOS: Learning What You Don’t Know by Virtual Outlier Synthesis"
deeplearning-wisc's Repositories
deeplearning-wisc/vos
source code for ICLR'22 paper "VOS: Learning What You Don’t Know by Virtual Outlier Synthesis"
deeplearning-wisc/knn-ood
Code for ICML 2022 paper "Out-of-distribution Detection with Deep Nearest Neighbors"
deeplearning-wisc/stud
source code for CVPR'22 paper "Unknown-Aware Object Detection: Learning What You Don’t Know from Videos in the Wild"
deeplearning-wisc/MCM
PyTorch implementation of MCM (Delving into out-of-distribution detection with vision-language representations), NeurIPS 2022
deeplearning-wisc/dream-ood
source code for NeurIPS'23 paper "Dream the Impossible: Outlier Imagination with Diffusion Models"
deeplearning-wisc/cider
PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023
deeplearning-wisc/gradnorm_ood
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
deeplearning-wisc/npos
source code for ICLR'23 paper "Non-parametric Outlier Synthesis"
deeplearning-wisc/react
Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"
deeplearning-wisc/multi-label-ood
deeplearning-wisc/dice
Code for ECCV 2022 paper "DICE: Leveraging Sparsification for Out-of-Distribution Detection"
deeplearning-wisc/MOOD
Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection
deeplearning-wisc/args
deeplearning-wisc/opencon
Code for TMLR 2023 paper "OpenCon: Open-world Contrastive Learning"
deeplearning-wisc/siren
source code for NeurIPS'22 paper "SIREN: Shaping Representations for Detecting Out-of-Distribution Objects"
deeplearning-wisc/poem
PyTorch implementation of POEM (Out-of-distribution detection with posterior sampling), ICML 2022
deeplearning-wisc/vit-spurious-robustness
deeplearning-wisc/picle
Official code for ICML 2024 paper on Persona In-Context Learning (PICLe)
deeplearning-wisc/Spurious_OOD
deeplearning-wisc/haloscope
source code for NeurIPS'24 paper "HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection"
deeplearning-wisc/hypo
deeplearning-wisc/NSCL
Code for ICML 2023 paper "When and How Does Known Class Help Discover Unknown Ones? Provable Understandings Through Spectral Analysis"
deeplearning-wisc/sal
source code for ICLR'24 paper "How does unlabeled data provably help OOD detection?"
deeplearning-wisc/PG-DRO
Official Implementation of AAAI 2023 paper "Distributionally Robust Optimization with Probabilistic Groups"
deeplearning-wisc/scone
deeplearning-wisc/sorl
Code for NeurIPS 2023 paper "A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning"
deeplearning-wisc/id_label
source code for ICML'24 paper "When and how does in-distribution label help out-of-distribution detection?"
deeplearning-wisc/ink
deeplearning-wisc/SNN
Official Implementation of AAAI 2024 "How to Overcome Curse-of-Dimensionality for OOD Detection?" paper
deeplearning-wisc/graph-spectral-ood
[NeurIPS 2024] Official Implementation of "Bridging OOD Generalization and Detection: A Graph-Theoretic View"